• Title/Summary/Keyword: Fake Identity

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Enhanced Hybrid Privacy Preserving Data Mining Technique

  • Kundeti Naga Prasanthi;M V P Chandra Sekhara Rao;Ch Sudha Sree;P Seshu Babu
    • International Journal of Computer Science & Network Security
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    • v.23 no.6
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    • pp.99-106
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    • 2023
  • Now a days, large volumes of data is accumulating in every field due to increase in capacity of storage devices. These large volumes of data can be applied with data mining for finding useful patterns which can be used for business growth, improving services, improving health conditions etc. Data from different sources can be combined before applying data mining. The data thus gathered can be misused for identity theft, fake credit/debit card transactions, etc. To overcome this, data mining techniques which provide privacy are required. There are several privacy preserving data mining techniques available in literature like randomization, perturbation, anonymization etc. This paper proposes an Enhanced Hybrid Privacy Preserving Data Mining(EHPPDM) technique. The proposed technique provides more privacy of data than existing techniques while providing better classification accuracy. The experimental results show that classification accuracies have increased using EHPPDM technique.

Direction of Global Citizenship Education in the Age of Infodemic : A Case Study of the COVID-19 Pandemic in Korea

  • Jisu Park
    • International journal of advanced smart convergence
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    • v.12 no.1
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    • pp.82-91
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    • 2023
  • In 2020 when the COVID-19 pandemic began in full-scale, the WHO Director-General warned of the dangers of an infodemic. The infodemic is a phenomenon in which false information spreads rapidly like an epidemic and causes chaos, and it was noted that the COVID-19 pandemic is not just limited to health problems, but also linked to a variety of issues such as human rights, economic inequality, various discrimination, hate speech, fake news, global governance etc. In the field of education, it is necessary to think about how to connect this global situation with school classes. Accordingly, this study suggested the direction for global citizenship education by analyzing how the infodemic spreads on Korean social media with the case of the recent global COVID-19 pandemic. According to the research results, the rate of negative emotions was higher than positive ones in the emotions that generate infodemic, while anxiety and anger were focused among negative emotions. In addition, the infodemic tended to spread widely with the feelings of anger rather than anxiety, and the feelings of anger led to advocating aggressive policies against certain country and regions. Therefore, global citizenship education is required to focus on a sense of duty and responsibility as a citizen, not on the level of national identity based on an exclusive sense of belonging. Furthermore, global citizenship education needs to lead to presenting a blueprint for education in a way that can enhance the awareness of the global community for joint response to global challenges and realize common prosperity based on sustainability and justice.

Cascaded-Hop For DeepFake Videos Detection

  • Zhang, Dengyong;Wu, Pengjie;Li, Feng;Zhu, Wenjie;Sheng, Victor S.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.5
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    • pp.1671-1686
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    • 2022
  • Face manipulation tools represented by Deepfake have threatened the security of people's biological identity information. Particularly, manipulation tools with deep learning technology have brought great challenges to Deepfake detection. There are many solutions for Deepfake detection based on traditional machine learning and advanced deep learning. However, those solutions of detectors almost have problems of poor performance when evaluated on different quality datasets. In this paper, for the sake of making high-quality Deepfake datasets, we provide a preprocessing method based on the image pixel matrix feature to eliminate similar images and the residual channel attention network (RCAN) to resize the scale of images. Significantly, we also describe a Deepfake detector named Cascaded-Hop which is based on the PixelHop++ system and the successive subspace learning (SSL) model. By feeding the preprocessed datasets, Cascaded-Hop achieves a good classification result on different manipulation types and multiple quality datasets. According to the experiment on FaceForensics++ and Celeb-DF, the AUC (area under curve) results of our proposed methods are comparable to the state-of-the-art models.

An Analysis of Posthuman's Body Type and Fashion in SF Movies (SF 영화에 나타난 포스트휴먼의 신체 유형 및 패션 분석)

  • Choi, Jung-Hwa
    • The Research Journal of the Costume Culture
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    • v.19 no.3
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    • pp.473-487
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    • 2011
  • The purpose of this study is to analyze the body type and fashion of posthuman in SF movies. The method of this study was to analyze documentaries, internet web site, fashion books and so forth. The results were as follows: The body types of posthuman were expressed as mutation type, prosthetic type, clone type by biological hybrid or renovation and digital type by computer simulation. The mutation type was expressed as reinforcement of masculinity or feminity and reinforcement of body functions. The fashion item was expressed as a black tailored suit, leather jacket, cat suit, whip, black sunglass, garter belt, high heel shoes, short pants, black one piece dress and functional body suit. The prosthetic type was expressed as reinforcement of body functions and reinforcement of masculinity or feminity. The fashion item was expressed as a military item, high-tech power suit and ergonomic armor suit. The clone type was expressed as the plural ego with reinforcement of body functions. The fashion item was expressed as a power shoulder jacket, fake fur coat, vinyl, black see-through look and functional suit. The digital type was expressed as reinforcement of masculinity or feminity and the plural ego with reinforcement of body functions. The fashion item was expressed as a data suit, leather jacket, black over coat, boots, black sun glass, ethnic items and military items. The meanings of posthuman fashion in SF movies were impurity of posthuman, display of superhuman's power by sexuality, metaphor of power and fantasy of superhero in opposition futuristic dystopia. As mentioned above, posthuman body type and fashion in SF movies become the conversational topic in the real world. The fact that we think about utopia and identity of posthuman in the future is of great significance.

Development of a Standardized Framework for Domestic Information Security Education; Focusing on a Two-Track Curriculum Customized by Age and Job (국내 정보보호 교육 표준 프레임워크 개발; 연령 및 직무 맞춤의 이원화(Two-track) 교육과정을 중심으로)

  • Park, Minjung;Lee, GI Hyouk;Chai, Sangmi
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.31 no.5
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    • pp.1083-1095
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    • 2021
  • With the recent increase in users' dependence on the Internet and the spread of various IT devices, the influence of information security on the users' has expanded compared to the past. Therefore, it is expected to have an increased influence on information security in personal life. In addition, as the intrusion factors that threaten security continue to become more advanced and diversified (eg., fake news, cyberbullying, identity theft), the need for nurturing information security experts is increasing. Furthermore, not only corporate information security workers, but also all individuals, cannot be free from the threat of information security. Therefore, it is necessary to prepare various information security education to improve information security awareness and induce proactive information security behaviors. In this study, characteristics of domestic and foreign information security education courses are analyzed and provide a standardized framework for information security education applicable to the domestic environment.

Extraction of System-Wide Sybil-Resistant Trust Value embedded in Online Social Network Graph (온라인 소셜 네트워크 그래프에 내포된 시스템-차원 시빌-저항 신뢰도 추출)

  • Kim, Kyungbaek
    • KIPS Transactions on Computer and Communication Systems
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    • v.2 no.12
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    • pp.533-540
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    • 2013
  • Anonymity is the one of main reasons for substantial improvement of Internet. It encourages various users to express their opinion freely and helps Internet based distributed systems vitalize. But, anonymity can cause unexpected threats because personal information of an online user is hidden. Especially, distributed systems are threatened by Sybil attack, where one malicious user creates and manages multiple fake online identities. To prevent Sybil attack, the traditional solutions include increasing the complexity of identity generation and mapping online identities to real-world identities. But, even though the high complexity of identity generation increases the generation cost of Sybil identities, eventually they are generated and there is no further way to suppress their activity. Also, the mapping between online identities and real identities may cause high possibility of losing anonymity. Recently, some methods using online social network to prevent Sybil attack are researched. In this paper, a new method is proposed for extracting a user's system-wide Sybil-resistant trust value by using the properties embedded in online social network graphs. The proposed method can be categorized into 3 types based on sampling and decision strategies. By using graphs sampled from Facebook, the performance of the 3 types of the proposed method is evaluated. Moreover, the impact of Sybil attack on nodes with different characteristics is evaluated in order to understand the behavior of Sybil attack.

Personal Information Overload and User Resistance in the Big Data Age (빅데이터 시대의 개인정보 과잉이 사용자 저항에 미치는 영향)

  • Lee, Hwansoo;Lim, Dongwon;Zo, Hangjung
    • Journal of Intelligence and Information Systems
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    • v.19 no.1
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    • pp.125-139
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    • 2013
  • Big data refers to the data that cannot be processes with conventional contemporary data technologies. As smart devices and social network services produces vast amount of data, big data attracts much attention from researchers. There are strong demands form governments and industries for bib data as it can create new values by drawing business insights from data. Since various new technologies to process big data introduced, academic communities also show much interest to the big data domain. A notable advance related to the big data technology has been in various fields. Big data technology makes it possible to access, collect, and save individual's personal data. These technologies enable the analysis of huge amounts of data with lower cost and less time, which is impossible to achieve with traditional methods. It even detects personal information that people do not want to open. Therefore, people using information technology such as the Internet or online services have some level of privacy concerns, and such feelings can hinder continued use of information systems. For example, SNS offers various benefits, but users are sometimes highly exposed to privacy intrusions because they write too much personal information on it. Even though users post their personal information on the Internet by themselves, the data sometimes is not under control of the users. Once the private data is posed on the Internet, it can be transferred to anywhere by a few clicks, and can be abused to create fake identity. In this way, privacy intrusion happens. This study aims to investigate how perceived personal information overload in SNS affects user's risk perception and information privacy concerns. Also, it examines the relationship between the concerns and user resistance behavior. A survey approach and structural equation modeling method are employed for data collection and analysis. This study contributes meaningful insights for academic researchers and policy makers who are planning to develop guidelines for privacy protection. The study shows that information overload on the social network services can bring the significant increase of users' perceived level of privacy risks. In turn, the perceived privacy risks leads to the increased level of privacy concerns. IF privacy concerns increase, it can affect users to from a negative or resistant attitude toward system use. The resistance attitude may lead users to discontinue the use of social network services. Furthermore, information overload is mediated by perceived risks to affect privacy concerns rather than has direct influence on perceived risk. It implies that resistance to the system use can be diminished by reducing perceived risks of users. Given that users' resistant behavior become salient when they have high privacy concerns, the measures to alleviate users' privacy concerns should be conceived. This study makes academic contribution of integrating traditional information overload theory and user resistance theory to investigate perceived privacy concerns in current IS contexts. There is little big data research which examined the technology with empirical and behavioral approach, as the research topic has just emerged. It also makes practical contributions. Information overload connects to the increased level of perceived privacy risks, and discontinued use of the information system. To keep users from departing the system, organizations should develop a system in which private data is controlled and managed with ease. This study suggests that actions to lower the level of perceived risks and privacy concerns should be taken for information systems continuance.